The approaches described in this section could be pursued, but are not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated herein, the approaches described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
The use of electronic message communication systems has increased significantly in the recent past. However, numerous users of such systems, whether they are message senders or receivers, find such systems inconvenient and cumbersome to use. Similar problems are associated with telephone, facsimile, and e-mail communications, and others.
In the e-mail context, in one past approach, senders marketing commercial products or services would acquire or develop lists of e-mail addresses and then periodically send mass unsolicited e-mail messages (“spam”) to all addresses in the lists. Using modern electronic systems, the cost of sending millions of such messages has been negligible, and a response rate of even less than one percent has been considered worthwhile. Thus, successful delivery of unsolicited messages to valid in-boxes of recipients normally translates into income for the sender.
Unfortunately, this approach causes receivers to receive unwanted messages. The direct and indirect costs of receiving “spam” are high. In response, receivers have adopted a variety of approaches to prevent receipt or viewing of unwanted messages.
In one approach, receivers use filtering, marking, or blocking technologies that attempt to classify messages as “spam” or not spam by examining various aspects of the message. For example, some filters look for keywords in the message subject line and reject or quarantine messages that contain keywords matching a list of prohibited words. In another approach, receivers use “blacklists” to identify and prohibit or less easily admit messages from suspect senders of unsolicited messages. Some receivers augment these technologies with personal “white lists” of friends or other acceptable senders; messages from senders in the white list are admitted or more easily admitted. The white lists and blacklists also may come from networked sources. Techniques for performing blacklist lookups are described at the “ip4r” HTML document that is available online at the time of this writing at the “support” subdirectory of the “junkmail” directory of the “declude” commercial domain of the World Wide Web, and at the “bill” section of the “scconsult” commercial domain of the World Wide Web. Example blacklists include the series of blacklists provided by the “njabl” organization domain of the World Wide Web. Example white lists could include lists of Fortune 500 companies and other reputable senders.
One problem with these approaches is that some messages that receivers want may not reach the intended receivers because they are identified as “spam” by the filtering or blocking technologies. Receivers who use filtering or blocking technologies regularly fail to receive some legitimate messages because the filtering and blocking technologies cannot always properly distinguish legitimate messages from unsolicited messages. For example, certain industry-standard terms or technical abbreviations may be identical to prohibited keywords, confusing the “spam” filter.
Further, receivers continue to receive large volumes of unwanted messages that are not properly trapped by the “spam” filter. As a result, many receivers now refuse to disclose their address except under limited circumstances. In response, many legitimate senders, such as reputable commercial enterprises, have developed “opt-in” procedures in which the addresses of receivers, such as customers, are not used at all unless the receiver affirmatively agrees to receive messages. Even when this is done, the filtering or blocking technologies may delete or quarantine even those messages from legitimate senders that are directed to receivers who have “opted in.” Consequently, the value of e-mail as a marketing tool for responsible communications directed to receivers who have “opted in” is decreasing. Many receivers remain essentially defenseless to the daily onslaught of “spam” arriving in their e-mail in-boxes. Whereas many states have enacted legislation that imposes civil or criminal penalties for sending “spam,” these remedies are time-consuming for receivers to pursue. In addition, while many Internet Service Providers (“ISPs”) actively identify and refuse to communicate or do business with those who send “spam,” however, policing such improper activity imposes a significant cost on the ISP. In addition, ISPs are burdened with the aggregated network and disk usage costs associated with the sending and receiving the unwanted messages. End users may also be burdened with bandwidth costs associated with downloading these messages.
ISPs also incur costs associated with processing messages directed to recipients who do not hold an account with the ISP. For these recipients, the ISPs mail system typically generates an automatic “bounce” message that states that the recipient is unknown. Indeed, a “double bounce” may occur when a message bears an invalid sender address, and is sent to an invalid recipient. Costs are associated with maintaining the equipment, network bandwidth, and software that generates the bounce messages and for dispatching the bounce messages back into the network to the sender. Thus, there is a need for a system or method that can reduce the number of “bounce” and “double bounce” events experienced by ISPs and derived from unwanted messages.
Thus, the problem of “spam” in the Internet e-mail context is essentially a war of attrition. There are legitimate marketing organizations that send promotional messages by bulk e-mail, and other senders who send valid bulk messages. In general, however, no one benefits from the activities of “spammers,” other than the “spammers” themselves. ISPs, business enterprises, and end users all suffer inconvenience, costs, and annoyances.
Even when ISPs and enterprises use anti-“spam” technologies, large numbers of “spam” messages may not be identified as spam, and many non-spam messages may be misclassified as spam. This costs e-mail marketers, and causes senders to lose confidence in the benefits of e-mail marketing. Moreover, end users are required to invest time in monitoring, checking, delivering, and negotiating blacklists, white lists, and similar mechanisms. The information from these lists can be conflicting, and therefore making a decision for a particular email sender based on the information in these lists can be difficult.
While the foregoing example problems exist in the context of e-mail, instant messaging, chat-room applications, Web message boards, telephone, and facsimile communications suffer from analogous problems.